Real-time agent performance, alerting, and SLA tracking in n8n agents — without rewriting your code, without adding a proxy to the request path.
The problem
n8n is great at what it does, but production-grade monitoring is bring-your-own. Most teams discover this when the first production incident hits, the first OpenAI bill arrives, or the first auditor asks for evidence.
Specifically:
- No native cost visibility per workflow or AI Agent node
- AI Agents can call HTTP Request against production with no review
- Workflows that loop on a failing tool can rack up $1000s before detection
How Prefactor solves it
Prefactor wraps your n8n Workflow and adds monitoring as a runtime layer. Specifically:
- alert on quality regression after a prompt change
- alert when p95 latency exceeds SLA
- monitor agent error rates per environment
- track success rates per intent
- dashboard for on-call view of agent health
Install and integrate
Install via n8n Community Nodes// In n8n:
// Settings → Community Nodes → install n8n-nodes-prefactor
// Add "Prefactor: Wrap Workflow" node at workflow start
// Or use webhook integration for n8n Cloud (no install)Specific use cases
- Alert on quality regression after a prompt change
- Alert when p95 latency exceeds sla
- Monitor agent error rates per environment
- Track success rates per intent
- Dashboard for on-call view of agent health
FAQ
Does this add latency? Per-span instrumentation adds ~2-5ms. Telemetry ships asynchronously. No synchronous network call in the agent's hot path unless you enable blocking policy enforcement.
Can I configure this per-agent? Yes. Monitoring settings are per-agent — different agents can have different policies, sampling rates, retention, etc.
Is this compatible with other observability tools? Yes. Prefactor exports OpenTelemetry; works alongside Datadog, Langfuse, LangSmith, and others.
Related
Start free
[Get started free →] [Book a demo →]